OXplus improves operational reliability with Asset Performance Management. Empower your OT and IT leaders with essential insights into remote monitoring, asset health, and predictive maintenance to ensure your business never stops.
Asset Performance Management
ASSET PERFORMANCE MANAGEMENT
APM Predict
APM – Predictive Maintenance Insights is part of OXplus’ Asset Performance Management (APM) portfolio. The solution focuses on the needs of maintenance managers and reliability engineers to identify risks and optimize asset reliability. It looks for patterns in asset data, how the asset is being used, and the environment in which it is operating.
Predictive Maintenance Insights predicts asset health using statistical models and machine learning. Includes failure date/probability, key drivers, degradation curves, and anomaly detection. It can predict failures based on build asset failure models, determined factors that contribute to failure and based on sensor data.
The benefits are:
1. Reduced failures
2. Reduced maintenance costs
3. Improved asset utilization
4. Extended life of asset
5. Increased production output

ASSET PERFORMANCE MANAGEMENT
APM Health
IBM released new capabilities of Maximo Asset Health Insights in MAHI 7602. MAHI is designed for the reliability engineer in mind, and brings all of the information needed by the engineer into one place. It is fully integrated with the Watson IoT Platform and analytics capabilities, and it leverages the new UI/UX technology available for Maximo. Asset Health also enables the reliability engineer from right within Maximo to leverage their knowledge to define the asset health calculation by asset class which can include a rich combination of sensor data and/or any other object within the asset record. It allows them various drill down views into the data, and provides context based actions for them to achieve optimal results.
They can define warnings and notifications which can be leveraged to take actions prior to a potential failure. They can initiate or work on investigations into failure incidents for minimize risk, and can analyze their PM program to uncover areas of inefficiencies such as ineffective job plans, or corrective maintenance that could have been avoided through preventive maintenance. This new release also provides insights into key decisions around when an asset needs to be refurbished or replaced, informed by the health of the asset.
Watson IoT helps businesses make smarter decisions about asset management by augmenting IoT data with powerful cognitive insights. The resulting dashboard display of health scoring provides evidence on which to base operational decisions.
Asset Performance Management represents a new way of maintaining equipment—one based not only on current condition-based readings coming from the equipment, but also informed by other influences like age, maintenance history, weather incidents and subcomponents with their own historical context. These data sources are analyzed by the Watson IoT Platform which feeds results back to Maximo, providing users with an overall assessment and score of asset health.
The benefits are:
1. Reduce fleetwide operational risk by focusing on the right assets
2. Increase asset availability
3. Reduce unnecessary preventive maintenance
4. Reduce time to make capital replacement planning decisions
ASSET PERFORMANCE MANAGEMENT
APM Asset Monitor
Our Asset Monitor leverages our deep commitment to data science at enterprise scale to remotely monitor critical assets and operations, improve anomaly detection with AI, and enable root‐cause analysis so that teams can proactively address challenges and avoid surprises.
Your asset maintenance and operational teams struggle with visibility across operations due to fragmented legacy systems and data silos. Alerts are numerous and fixed notification parameters fail to provide the right context. The result? True anomaly detection is unavailable causing availability, cost, and risk KPIs to suffer. The convergence of IT systems and operational systems is no longer an option. It is a necessity. It is now possible to capture data directly from low cost sensors, legacy control systems, and other repositories that have been collecting data for years.
Asset Monitor uses sensor and SCADA data, alongside machine learning, to create custom models. Associate data points, assets, and hierarchies and visualize data over time. Monitor provides a customizable dashboard for operations and systems.
The benefits are:
1. Enterprise level data aggregation & visibility
2. Scale operations across processes and sites
3. AI-based detection of issues
4. Enable drill down analysis for resolution team
5. Extensible IoT foundation